Probabilistic Methods for Bioinformatics

Author: Richard E. Neapolitan
Publisher: Morgan Kaufmann
ISBN: 9780080919362
Format: PDF, Mobi
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The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics. Shares insights about when and why probabilistic methods can and cannot be used effectively; Complete review of Bayesian networks and probabilistic methods with a practical approach.

Foundations of Algorithms

Author: Richard Neapolitan
Publisher: Jones & Bartlett Publishers
ISBN: 1449600166
Format: PDF, Docs
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Foundations of Algorithms, Fourth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. The volume is accessible to mainstream computer science students who have a background in college algebra and discrete structures. To support their approach, the authors present mathematical concepts using standard English and a simpler notation than is found in most texts. A review of essential mathematical concepts is presented in three appendices. The authors also reinforce the explanations with numerous concrete examples to help students grasp theoretical concepts.

Bioinformatics

Author: Yu Liu
Publisher: CRC Press
ISBN: 1482246627
Format: PDF
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This title includes a number of Open Access chapters. The book introduces bioinformatic and statistical methodology and shows approaches to bias correction and error estimation. It also presents quantitative methods for genome and proteome analysis.

Probabilistic Modeling in Bioinformatics and Medical Informatics

Author: Dirk Husmeier
Publisher: Springer Science & Business Media
ISBN: 1846281199
Format: PDF, Docs
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Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Encyclopedia of Bioinformatics and Computational Biology

Author:
Publisher: Elsevier
ISBN: 0128114320
Format: PDF, ePub, Mobi
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Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

Artificial Intelligence

Author: Richard E. Neapolitan
Publisher: CRC Press
ISBN: 1351384392
Format: PDF
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The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.

Probabilistic Modeling in Bioinformatics and Medical Informatics

Author: Richard Dybowski
Publisher:
ISBN: 9786610346653
Format: PDF, Mobi
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Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Bioinformatics Research and Applications

Author: Ion Măndoiu
Publisher: Springer Science & Business Media
ISBN: 3540794492
Format: PDF, Mobi
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th The 4 edition of the InternationalSymposium on BioinformaticsResearchand Applications (ISBRA 2008) was held on May 6-9, 2008 at Georgia State U- versity in Atlanta, Georgia. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications. The technical program of the symposium included 35 contributed papers, selected by the Program Committee from a number of 94 full submissions - ceived in response to the call for papers. The technical program also included six papers contributed to the First International Workshop on Optimal Data Mining in Gene Expression Analysis (ODGEA 2008), which was held in c- junction with ISBRA 2008. In addition to the contributed papers, the sym- sium included tutorials and poster sessions and featured invited keynote talks by six distinguished speakers. Andrew Scott Allen from Duke University and Dan Nicolae from the University of Chicago spoke on novel analysis methods for genome-wide association studies; Kenneth Buetow, director of the National Cancer Institute Center for Bioinformatics, spoke on the cancer Biomedical - formatics Grid; Andrey Gorin from Oak Ridge National Laboratory spoke on peptide identi?cation from mass spectrometry data; Yury Khudyakov from the Center for Disease Control and Prevention spoke on integrative viral molecular epidemiology; and Kwok Tsui from Georgia Institute of Technology spoke on data mining and statistical methods for analyzing microarray experiments.

Bayesian Methods in Structural Bioinformatics

Author: Thomas Hamelryck
Publisher: Springer
ISBN: 3642272258
Format: PDF, Kindle
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This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.

Pattern Recognition in Bioinformatics

Author: Visakan Kadirkamanathan
Publisher: Springer Science & Business Media
ISBN: 3642040306
Format: PDF, ePub, Mobi
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This book constitutes the refereed proceedings of the Fourth International Workshop on Pattern Recognition in Bioinformatics, PRIB 2009, held in Sheffield, UK, in September 2009. The 38 revised full papers presented were carefully reviewed and selected from numerous submissions. The topics covered by these papers range from image analysis for biomedical data to systems biology. The conference aims at crating a focus for the development and application of pattern recognition techniques in the biological domain.